Modern digital cameras offer a feature known as “automatic white balancing” which is a process used to adjust the color balance of an image captured by the camera under varying illumination conditions. Conventional white balancing algorithms attempt to attain the same high level of color constancy associated with most human color perception systems by removing unrealistic color casts captured by the camera when acquiring the image. In doing so, these algorithms generally first determine a scene illuminant used to illuminate the captured image. Once determined, the scene illuminant's impact on the captured scene may be neutralized to obtain a more color balanced, aesthetically pleasing image.
Often, in determining the illuminant, conventional white balancing algorithms require a calibration process in which the user must first capture a reference image so that future images captured by the camera may be white balanced. However, these algorithms are often not equipped to handle situations in which the camera may not be able to perform these calibrations. For example, the camera may not have access to scenes with these required reference points and, thus, may produce unappealing resultant images. As a result, the user may have to manually manipulate each image of interest in order to attain a more color balanced image. This process may prove to be especially cumbersome if the user wishes to white balance several images at a time and may lead to user frustration.